Today systems for distributing traffic related information (like for example road hazard warnings, traffic density information, traffic warning) exist. Most events, like road hazard information or traffic warnings, contain (among others properties) geographic information. This may comprise a geographic location or a geographic extend, describing where the event is happening, and also geographic information about the affected region.
For example, a particular traffic jam might have a length of 2 km and affects driving for 25 km behind it. It is beneficial to not distribute such information to not affected service users (in the above example to service users not located in the affected region) in order to not load those users and the network with information that does not have any relevance. From network perspective this saves bandwidth.
In order to achieve this first the traffic jam must be detected (for example by monitoring the amount of users in the geographical target area) and second the network area (covering the geographical target area) must be identified where the information about the jam shall be distributed. The identified network area would ideally match with the geographical target area in order to avoid reaching not affected users and so wasting network resources. However the granularity for partitioning a network into areas may be limited due to technical reasons.
For monitoring the amount of users in a geographical area, and informing them in case of for example a hazard warning, mobile networks may be utilized. A server shall be aware where the mobile user (for example the car or a mobile device in the car) is located. Existing tracking/location areas in the mobile system are too coarse for this purpose. Therefore the concept of a “Geo Location Messaging (GLM)” grid is introduced in WO 2012/055433 A1 where a user sends a Geo Messaging location update message each time when he crosses a grid line and so let the GLM system be aware about its location. By dimensioning the grid size reasonably a suitable granularity can be achieved without loading the system with Geo Messaging related location update messages too much.
Current GLM systems operate in the two-dimensional space. Position related data, which the device (for example a client) is sending to the GLM Server, comprises altitude and longitude to indicate its position on a two-dimensional map. However two-dimensional Geo Messaging faces the problem that it is not possible to distinguish between positions which differ in height, like for example for drones or airplanes changing altitudes during a flight. Also, the two-dimensional GLM system cannot differentiate between two vehicles which are driving on different road segments that physically overlap. Those types of road constructions are for instance standard in Japan and occur also in the USA.
More sophisticated GLM techniques are needed due to the different properties of for example drones compared to cars (drones are fast, not bound to streets and require significant skills to fly). Due to those properties drones (or comparable vehicles) are more prone to crashes. Furthermore the less regulated nature of the space where drones move poses additional challenges for the GLM system (compared to for example streets with defined traffic routes, rules and regulation by means like for example traffic lights).